IBM Cloud Logs, a log managment tool, turns log data into actionable insights, reducing operational costs and boosting system reliability. Fully integrated with IBM Cloud, IBM Cloud Logs allows quick issue detection, performance optimization, and ensures strong security compliance without traditional log indexing overhead.
The lab setup includes an instance of IBM Cloud Logs that you will use to explore some of its features. Platform data, platform logs and auditing events are collected automatically.
Logs generated by a Kubernetes cluster are also available. A logging agent is deployed on the Kubernetes cluster to collect and send logs to the IBM Cloud Logs instance.
In this hands-on lab, you will learn about IBM Cloud Logs features.
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Go the Logging section under Observability.
Alternatively, use the Navigation menu ☰ > Observability > Logging > Instances.
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Launch the Logging Dashboard.
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The UI opens in the Home dashboard is a predefined dashboard that includes the following information for the time frame selected for the dashboard:
- The trend of high severity logs and their percentage of total logs.
- The trend of metric ingestion.
- A list of triggered alerts grouped by severity.
- A list of anomalies grouped by type.
- The applications and subsystems that generated the highest volume of errors and their template distributions.
- The logs volumes grouped by severity.
- The top 3 errors that occurred above their usual occurrence rates or occurred for the first time within the last 7 days.
- Information on the application and subsystem combinations with the highest error rates.
By default the displayed timeframe is set to 24 hours, and the information included covers both logs and metrics.
At a glance, you can see the type of logs that you are ingesting, their priority, the volumes per priority, the top errors, and the recent alerts that have been triggered.
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Cloud Logs includes many different features grouped in the following sections.
The patient application that you previously deployed in the OpenShift cluster within a namespace named after your username generates logs.
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Let's re-use the same commmand we load in the section before to generate some requests, this will in turn generate logs.
while sleep 1; do curl -s https://$HOST/info; done
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Click on the Logging tab.
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In the Cloud Logs dashboard, click Explore logs > Logs.
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Under Application, select the namespace named after your username to view the logs you generated.
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Change the Severity to Debug.
You can use a view to see logs that match a specific filtering criteria. Views can be grouped into folders. View names must be unique within a folder.
In the left-hand navigation, click Explore logs > Logs. By default, the last view you had opened will be displayed. If no view was previously open, all views will be displayed.
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Select the fields to be included in the view. By default, you can select Applications, Subsystems, and log Severities.
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Select the application that matches the namespace allocated to you.
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Select the subsystem patient-ui.
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Select if you want your view to only include Priority Logs (those in the Priority Insights data pipeline or All Logs, that is, logs that are stored in your data bucket. Logs in the data bucket include logs collected through all the three data pipelines.
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Add a Lucene query " in-memory data" to further filter your data.
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Specify the time interval for the view, for example Last 5 minutes.
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Save your view by clicking the three dots ...
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Set the view name to -first-view.
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Check Save query and filters to save the query and filter values you configured.
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Set the privacy of your view to Private.
Private views can only be seen by you. You can set a view as Private or Shared.
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Click Create.
Good job! You have completed the lab. Note that you can do much more in Cloud Logs such as setting Alerts.
- Find more about IBM Cloud Logs in the IBM Cloud documentation
- Managing the Logging agent for IBM Cloud Kubernetes Service clusters